We have stumbled into the era of machine psychologyOf course, neural networks are commonly described as “black boxes” (often not quite deservedly). And historically, parts of psychology had its flirtations with cybernetics. But it is only recently that the we see a curious methodological convergence between these two fields – machine learning adopting methods of psychology...

Getting SmarterGeoffrey Hinton has a news bulletin for you: You’re not conscious...

Building Analytics at 500pxA look at building analytics from the ground up at a mid-sized start-up and some of the challenges faced along the way...

Emacs for Data ScienceIf you want an editor that works with R, python, SAS, Stata, SQL and almost any other data science language. If you want an editor with IDE-like features. If you want an editor that works on any platform and as well as on the terminal. If you're a fan of literate programming. If you want an editor that is highly customizable and will be around after most editors have come and gone, then you'd be hard pressed to find anything better than emacs....

Algorithmic Trading of Futures via Machine Learning
Algorithmic trading of securities has become a staple of modern approaches to financial investment. In this project, I attempt to obtain an effective strategy for trading a collection of 27 financial futures based sole y on their past trading data...

Jobs

The Uber Advanced Technology Center is the Pittsburgh division of the elite Uber Engineering Team; a high-performance culture marked by fearlessness and hyper-productivity. We focus on the development of key long-term technologies that advance Uber’s mission of bringing safe, reliable transportation to everyone, everywhere. Our research is primarily in the areas of mapping, vehicle safety, and autonomy. Our team is comprised of world-renowned researchers with decades of experience and we’re looking for superstar engineers who can work harder, faster, and smarter without sacrificing technical excellence...

Books

Simplifies machine learning for a broader audience and wider application by focusing on two algorithm families...

"I'm somewhat new to the field, working on a new venture involving predictive analytics. Of the resources I'm using, I keep coming back to this book - the background, problem setup, explanation of tradeoffs, and code examples have been really good..."